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documentation: add vignette for working with data #316

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a9d59ed
add datasets vignette
Apr 14, 2020
4ded252
update pkgdown.yml
Apr 14, 2020
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8 changes: 7 additions & 1 deletion _pkgdown.yml
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Expand Up @@ -22,6 +22,10 @@ navbar:
href: articles/deploy-to-aks/deploy-to-aks.html
- text: ---
- text: Guides
- text: Working with data
href: articles/guides/working-with-data.html
- text: Deploying models
href: articles/guides/deploying-models.html
- text: Troubleshooting
href: articles/guides/troubleshooting.html
- text: News
Expand Down Expand Up @@ -66,7 +70,7 @@ reference:
- '`wait_for_provisioning_completion`'
- '`list_supported_vm_sizes`'
- '`delete_compute`'
- title: Working with data
- title: Connecting to Azure Storage services
desc: Functions for accessing your data in Azure Storage services. A **Datastore** is attached to a workspace and is used to store connection information to an Azure storage service.
contents:
- '`upload_files_to_datastore`'
Expand Down Expand Up @@ -156,6 +160,7 @@ reference:
- '`log_row_to_run`'
- '`log_table_to_run`'
- '`view_run_details`'
- '`cran_package`'
- title: Hyperparameter tuning
desc: Functions for configuring and managing hyperparameter tuning (HyperDrive) experiments. Azure ML's HyperDrive functionality enables you to automate hyperparameter tuning of your machine learning models. For example, you can define the parameter search space as discrete or continuous, and a sampling method over the search space as random, grid, or Bayesian. Also, you can specify a primary metric to optimize in the hyperparameter tuning experiment, and whether to minimize or maximize that metric. You can also define early termination policies in which poorly performing experiment runs are canceled and new ones started.
contents:
Expand Down Expand Up @@ -213,3 +218,4 @@ reference:
- '`update_local_webservice`'
- '`delete_local_webservice`'
- '`reload_local_webservice_assets`'
- '`resource_configuration`'
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